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Pattern classification of cotton yarn neps

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Title Statement Pattern classification of cotton yarn neps
 
Added Entry - Uncontrolled Name Hasnat, Abdul ; Government College of Engineering & Textile Technology, 4 Cantonment Road, Barrack Square Berhampore, West Bengal-742 101, India
Ghosh, Anindya ; Government College of Engineering & Textile Technology, 4 Cantonment Road, Barrack Square Berhampore, West Bengal-742 101, India
Hoque, Azizul ; Kalyani University, Nadia, West Bengal-741 235
Halder, Santanu ; Kalyani Government Engineering College, Nadia, West Bengal-741 235
 
Uncontrolled Index Term Cotton yarn; Fibrous nep; Pattern classification; Probabilistic neural network; Seed coat nep; Support vector machine
 
Summary, etc. <p class="Abstract" style="text-align: justify;">In this study, two types of cotton yarn neps, viz. seed coat and fibrous neps, have been classified by means of two standard classifiers, namely support vector machine and probabilistic neural network using the features extracted from the images of neps. At first, the region of interest is located in the captured images using <em>k</em>-means clustering algorithm, from which six features are extracted. These extracted features are used as dataset (both training and testing) for classifiers. <br /> A <em>K</em>-fold cross validation technique has been applied to assess the performance of the two classifiers. The results show that the neps classification accomplished by means of image recognition through these classifiers achieves nearly 96-97% accuracy for the test data set. Experimental results show that the required time for training probabilistic neural network is significantly less as compared to that of support vector machine.</p>
 
Publication, Distribution, Etc. Indian Journal of Fibre & Textile Research (IJFTR)
2016-10-21 15:15:12
 
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http://op.niscair.res.in/index.php/IJFTR/article/view/7114
 
Data Source Entry Indian Journal of Fibre & Textile Research (IJFTR); ##issue.vol## 41, ##issue.no## 3 (2016): Indian Journal of Fibre & Textile Research
 
Language Note en